Method and apparatus for guidance of an operation of operating power plants

ABSTRACT

This invention refers to a .[.plant operating.]. method .Iadd.and apparatus for guidance of an operation .Iaddend.for overcoming an abnormal status of a plant. A plant data is detected from the plant, and all plant state members indicating an abnormality of the plant are identified from the plant data. The plant operating method .Iadd.and apparatus .Iaddend.includes .Iadd.apparatus for .Iaddend.estimating a cause whereby the plant status members are produced, predicting all plant status members arising after passing a given period of time according to the estimated cause, determining whether or not actual plant status members are present in the plant state members predicted and when the latter members are not present in the former members, repeatedly carrying out the processing of the steps of estimating and predicting to which the plant status members forcasted at the predicting step are inputted until all the actual plant status members come to exist in the plant status members forecasted at the predicting step. When all the actual plant status members are present in the plant status members predicted at the predicting step, a plant operation for overcoming the cause obtained at the step of estimating which produces the predicted plant status members is selected, and the plant operation is carried out according to the selected operation.

BACKGROUND OF THE INVENTION

This invention relates to a method .[.of.]. .Iadd.and apparatus forguidance such as .Iaddend.operating power plants, and particularly tothat by which a pertinent guide for operation can be provided to copewith an abnormality of the plants.

A method to utilize Cause-Consequence Tree (hereinafter referred to as"CCT") has been proposed hitherto for providing a guide for operation atthe time of a plant abnormality.

CCT is a process of putting the relation of cause and effect of aphenomenon taking place at a plant on the tree and is powerful tofunction when utilized for a guidance implementation of operation at thetime of a plant abnormality. However, a huge quantity of CCT will haveto be prepared to multiply the phenomenon with which the operation guideapparatus for a plant utilizing CCT is capable of coping, thus involvinga difficulty for implementation and maintenance.

Then, a technique of knowledge engineering which is utilized for amedical consultation system will be taken up as the technique forimplementation of a guidance system utilizing a small-scale data baseeffectively.

SUMMARY OF THE INVENTION

An .Iadd.object of this invention is to provide a method and apparatusfor guidance of an operation. Another .Iaddend.object of this inventionis to obtain a cause of an abnormality arising at a plant withprecision.

Another object of this invention is to obtain an optimal and secureoperation necessary to cope with an abnormality arising at a plant.

Further object of this invention is to minimize capacity of a data base.

A feature of this invention is to .Iadd.provide a method and apparatusto .Iaddend.repeat a processing comprising a step to decide an existenceof an actual plant state member in a forecasted plant state member andalso to estimate a cause of bringing about the state member, when thelatter member is not present in the former member, by inputting theforecasted plant state member until all the actual plant state memberscome to exist in the forecasted plant state member, and a step toforecast all the plant state members to arise after passing a givenperiod of time according to the cause so estimated.

FIG. 1 is a system diagram of an apparatus for putting a plant operatingmethod into practice which is given in one preferred embodiment of thisinvention to apply on a boiling water reactor plate;

FIG. 2 is an explanatory drawing representing an example of the contentsof a cause-consequence data base shown in FIG. 1;

FIG. 3 is an explanatory drawing representing an example of the contentsof a transition forecast data base shown in FIG. 1;

FIG. 4 is an explanatory drawing representing an example of the contentsof an operation data base shown in FIG. 1;

FIG. 5 is an explanatory drawing representing an example of the contentsof a particularization data base shown in FIG. 1;

FIG. 6 is an explanatory drawing representing an example of the contentsof a case data base shown in FIG. 1;

FIG. 7 and FIG. 8 are flowcharts of a processing program shown in FIG.1;

FIG. 9 is a block diagram of a data conversion division shown in FIG. 7;

FIG. 10 is a block diagram of a state grasp division shown in FIG. 7;

FIG. 11 is a block diagram of a cause enumeration division shown in FIG.7;

FIG. 12 is a block diagram of a forecast division shown in FIG. 7;

FIG. 13 is a block diagram of a non-contradiction confirmation divisionshown in FIG. 7;

FIG. 14 is a block diagram of a decision division shown in FIG. 7;

FIG. 15 is a block diagram of an operation enumeration division shown inFIG. 8;

FIG. 16 is a block diagram of a determination division shown in FIG. 8;

FIG. 17 is a block diagram of a particularization division shown in FIG.8;

FIG. 18 is a block diagram of an analogous case retrieval division shownin FIG. 8;

FIG. 19 is a block diagram of a guidance implementation division in FIG.8;

FIG. 20 is an explanatory drawing of a plant state signal outputted fromthe data conversion division;

FIG. 21 is an explanatory drawing of a plant state signal outputted fromthe state grasp division;

FIG. 22A and FIG. 22B are explanatory drawings of a plant state signaloutputted from the state grasp division in the cause decision division;

FIG. 23A and FIG. 23B are explanatory drawings of a plant state signaloutputted from the forecast division in the cause decision division;

FIG. 24A and FIG. 24B are explanatory drawings of a plant state signaloutputted from the cause enumeration division and the state graspdivision of the cause decision division called recursively;

FIG. 25 is an explanatory drawing of a plant state signal outputted fromthe state grasp division of the optimal operation determinationdivision;

FIG. 26A and FIG. 26B, FIG. 27A and FIG. 27B are explanatory drawings ofa plant state signal outputted from the forecast division and the stategrasp division of the optimal operation determination division calledrecursively.

A plant operating method which is given in one preferred embodiment ofthis invention to apply on a boiling water reactor plant will now bedescribed with reference to FIG. 1.

Steam generated at a core 2 in a reactor pressure vessel 1 is sent to aturbine 6 by way of a main steam pipe 13 and then condensed in acondenser 7 to water. The water is supplied into the reactor pressurevessel 1 as a cooling water by way of a feed-water piping 14. Thefeed-water piping 14 connects a condensate pump 8, a desalter 9,feed-water pumps 10A, 10B, 11A and 11B and a feed-water heater 12 fromthe upstream side in that order. The feed-water pumps 10A, 10B, 11A and11B are of motor-driven type. The feed-water pumps 11A and 11B aredriven temporarily for start-up and shutdown of a reactor but left instanby for backup of the feed-water pumps 10A and 10B during a normaloperation of the reactor. The feed-water pumps 10A and 10B are drivenall the time during operation of the reactor. The cooling water cominginto the reactor pressure vessel 1 is sent to the core 2 by way of a jetpump 3 by a recirculating pump 4 which is provided on a recirculatingsystem piping 5.

A water gauge 15 detects a water level (reactor level) 17 in the reactorpressure vessel 1. A flow meter 16 detects a discharge flowing in thejet pump 3. The sum of all discharges flowing in the jet pump 3 willindicate a quantity of the cooling water flowing in the core 2. Theprocess amount including the reactor level 17 and the jet pump dischargewhich are measured on various detectors is inputted to a centralprocessor 18B of an electronic computer 18 by way of a processinput/output unit 18A of the electronic computer 18. The electroniccomputer 18 has a memory (internal memory and external memory) 18C,besides. A consequence processed on the central processor 18B isdisplayed on a Braun tube (or CRT) 21 provided on a control panel 20.

The present embodiment comprises obtaining an operation guide for theabove reactor plant abnormality through utilizing a technique ofknowledge engineering, carrying out an operation at the time ofabnormality occurrence according to the guidance, thereby coping with anabnormal state of the reactor plant. Such operating method will bedescribed as follows. The memory 18C of the electronic computer 18stores a cause-consequence data base 22, a transition forecast data base23, an operation data base 24, a detail data base 25, a case data base26 and a processing program 27.

The cause-consequence data base 22 is that in which the relation ofcause and .[.effect.]. .Iadd.consequence .Iaddend.is recorded whichcomprises combining a cause .Iadd.or a premise .Iaddend.and aconsequence .Iadd.or a conclusion .Iaddend.to be determined directlyrelated to the cause .Iadd.as a rule.Iaddend.. This is a data storingarea which corresponds to that of the general "rule" as termed by peoplewho research knowledge engineering .Iadd.and which may be considered asa knowledge base storing area.Iaddend.. An example of thecause-consequence data base 22 in a boiling water reactor plant is shownin FIG. 2.

The transition forecast data base 23 is a data base for storinginformation to build up a data of the cause-consequence data base 22 inaccordance with the lapse of time. Stored herein are information on theoperating state of each equipment of the plant and the state of eachprocess amount and a technique to obtain, for the process amount forwhich a value representing the state has been obtained, a time to changethe value and a value after a certain time passes. An example of thetransition forecast data base 23 in a boiling water reactor plant isshown in FIG. 3.

FIG. 4 represents an example of the operation data base 24 in a boilingwater reactor plant. The operation data base 24 is a data base foradding a combination of a condition division and an operation plan witha combination of the state of each process amount and the operatingstate of each equipment of the plant as the condition division and anoperation then conceivable as the operation plan.

The detail data base 25 is a data base for recording a detail operatingmethod and operating limit of each equipment of the plant.

The case data base 26 is a data base for enclosing a consequence ofprior analysis and a record at the time of past operation.

The detail data base 25 and the case data base 26 in a boiling waterreactor plant are shown in FIG. 5 and FIG. 6, respectively.

An example of the processing program 27 will be described with referenceto FIG. 7 and FIG. 8. The processing program 27 consists of anabnormality detector portion 28, a data translator portion 30, a statusrecognizer portion 31, a cause decision division 32, an optimaloperation determination division 38, a detail searcher portion 42, anexample searcher portion 43 and a guidance implementation portion 44.The cause decision division 32 has a cause lister portion 33, a statusrecognizer portion 31, a predictor portion 34, a checker portion 35, arecursion controller portion 36 and a decider portion 37 of the causedecision division 32. Further, the optimal operation determinationdivision 38 has countermeasure lister portion 39, a predictor portion34, a status recognizer portion 31, a recursion controller portion 40and a selector portion 41 of the optimal operation determinationdivision 38.

The data translator portion 30 inputs a plant data which comes in ameasured process amount, unifies values of each plant data through alogical decision like majority decision, obtains a member state orstatus (an item to indicate one state of the plant) through combining anidentifier for the plant data and a consequence transformed into aspecial value in an apparatus to obtain a guidance for plant operationwhich indicates a value of the plant data in the processing given below(hereinafter referred to as "operation guide apparatus"), and thenoutputs these member states in a plant state signal. A flowchart of thedata translation portion 30 is shown in FIG. 9.

The status recognizer portion 31 compares each "cause" enclosed in thecause-consequence data base 22 with the inputted plant state signal andselects a "consequence" to come out according to the "cause"corresponding to the plant state signal. Then, the selected consequenceis added to the inputted plant state signal as a new member state. Aflowchart for the status recognizer portion 31 is shown in FIG. 10.

The cause lister portion 33 obtains a member state capable of causingeach member state of the inputted plant state signal or a combinationthereof through retrieving the "consequence" enclosed in thecause-consequence data base 22, thus outputting a retrieved.[."consequence".]. .Iadd."cause".Iaddend.. The flowchart is shown inFIG. 11.

The predictor portion 34 inputs the plant state signal and obtains thetime until values of each member state of the inputted plant statesignal change to those of the next level through executing a calculatingtechnique (program) stored in the prediction data base 23. Next, itselects the shortest time of those obtained as above and obtains thevalue of each member state after passing the shortest time also throughexecuting the calculating technique stored in the prediction data base23. Each member state is then unified and outputted as a plant statesignal for the next step. A flowchart of the precitor portion 34 isshown in FIG. 12.

The checker portion 35 inputs a reference plant state signal and asingle or plural plant state signal for which non-contradiction isconfirmed and outputs a plant state signal not included in the originalplant state signal and not including a member state taken in by the datatranslator portion 30. FIG. 13 shows a flowchart of thenon-contradiction confirmation division 35.

The decider portion 37 inputs a plurality of plant state signals andoutputs a plant state signal including each member state mostapproximate to each member state constituting the plant state signalinputted to the cause decision division 32. FIG. 14 shows the contents.

The countermeasure lister portion 39 inputs a plant state signal andlists to output operation plans then conceivable by retrieving thecondition division of the countermeasure data base 24. A flowchart ofthe countermeasure 39 is shown in FIG. 15.

The selector portion 41 inputs a plurality of plant state signals, ashsown in FIG. 16, and outputs the plant state signal most approximate tothe operation object then prevailing.

The cause decision division 32 inputs a plant state signal at the timeof a plant abnormality, actuates the cause lister portion 33, the statusrecognizer protion 31, the prediction portion 34, the checker portion35, the recursion controller portion 36 and the decider portion 37 todecide a cause of the plant abnormality, and then outputs the plantstate signal to which the cause is added. The plant state signaloutputted from the cause decision division 32, actuates thecountermeasure lister portion 39, the predictor portion 34, the statusrecognizer portion the recursion controller portion 40 and the selectorportion 41 to determine an optimal operating method, and outputs theplant state signal to which a consequence obtained through executing theoperation is added.

The detail searcher portion 42 inputs the plant state signal outputtedfrom the optimal operation determination division 38 and retrieves whatsignifies an operation of the equipment of the plant according to eachmember state of the plant state signal. And after ensuring that theretrieved operation satisfies an operation limit of the detail data base25, it adds a detail operation procedure to the plant state signal.Where the retrieved operation does not meet the operation limit of thedetail data base 25, it reruns the optimal operational determinationdivision 38. A flowchart of the detail searcher portion 42 is shown inFIG. 17.

The example searcher portion 43 inputs the plant state signal outputtedfrom the detail searcher portion 42, retrieves a cause and a keyword ofthe case data base 26 and adds that in which the cause coincides or thekeyword coincides with a member state of the plant state signal at aconstant rate or over to the plant state signal as an analogous case.

The guidance implementation portion 44 inputs the plant state signaloutputted for the example searcher portion 43 and changes the format tooutput it to CRT 21.

An operating method of a boiling water reactor plant on an apparatushaving the above-mentioned features will be described as follows.

While such a phenomenon will not be conceivable actually, the phenomenonwherein a shaft of the recirculating pump 4 to feed a cooling water tothe core 2 happens to adhere during operation of the boiling waterreactor plant is premised for description. When the shaft is adherent asmentioned, the quantity of a cooling water flowing in the core 2decreases and a void in the core 2 increases. The increase in void maylead to an ascent of the reactor level 17. Actually, a phenomenon of theshaft adherence and the void increase is not apparent but a processamount of the measured reactor level and the jet pump discharge is onlyknown. The reactor level 17 normally comes at a level L4. When thereactor level 17 reaches a level L8, the reactor is shut down urgently(scram). When the reactor level 17 reaches a level L7 immediately beforethe scram, an indication is given to that effect on the control panel20. An operator is thus acquainted with an ascent of the reactor level.A plant data representing a process amount of the reactor level 17 andthe jet pump discharge is inputted to the central processor 18B by wayof the input/output unit 18A. The inputted plant data is then subjectedto an analog-digital conversion so as to serve well for a processing inthe central processor 18B. Upon inputting the plant data, the centralprocessor 18B calls the processing program 27 (FIG. 7 and FIG. 8) whichis an operation guide apparatus in the memo 18C and performs a givenprocessing according to the processing program 27. The abnormalitydetector portion 28 determines a plant data indicating an abnormal valueof those which are inputted. When the plant data indicating an abnormalvalue (the reactor level 17 reaching L7 level in the case of thisembodiment) is present, a command 29 is outputted and contents of theabnormality are displayed on the control panel 20. When there is presentfurther such plant data indicating an abnormal value, the processingafter the data translator portion 30 of the processing program 27 isexecuted.

One or plural plant data 45 measured at the boiling water reactor plantis inputted to the data translator portion (FIG. 9) 30. Such data aswill not satisfy a set point (exceeding or coming lower) are allselected from the plant data 45 and then converted into a plate statesignal 46. The data translator portion 30 outputs the plant state signal46 shown in FIG. 20.

In the boiling water reactor plant, a plural detectors are provided foran important process amount like reactor level. Therefore, it must beensured that the measured results are coincident with each other. Ifnot, then an erroneous value measured on the detector which is so giventhrough a majority decision is prevented from being inputted to theoperation guide apparatus.

In FIG. 21, contents are given in ordinary characters, however, EBCDICcharacter code or integral number can be used practically.

The plant state signal 46 which is an output of the data translatorportion 30 is inputted to the status recognizer portion (FIG. 10) 31,which portions supplements information, if any, which is missing withthe plant state signal 46 shown in FIG. 20. Namely, the cause divisionof the cause-consequence data base 22 shown in FIG. 2 is retrievedaccording to each member state of the inputted plant state signal 46.Next, a decision is made on the retrieved result, and if "YES", theretrieved result is added to the plant state signal 46. After that, thecause division of the cause-consequence data base 22 is again retrieved.A decision is made on the retrieved result, and if "NO", then a plantstate signal 47 to which the above-mentioned retrieved result is addedis outputted. There is nothing to add in this embodiment, and the plantstate signal 47 similar to that of FIG. 20 which is shown in FIG. 21 isoutputted. In the embodiment, input and output of the status recognizerportion 31 are identical.

Since the time of occurrence of the abnormality is assumed for operationof the embodiment, a processing of the cause decision division 32 isexecuted by inputting the plant state signal 47.

The plant state signal 47 is inputted first to the cause lister portion33 in the cause decision division 32. With each member state of theplant state signal 47 as a "consequence", the cause lister portion 33retrieves the member state of the plant state signal 47 from aconsequence division of the cause-consequence data base 22 (FIG. 2) andadds an item of the cause division coping with the member state to theplant state signal 47. Namely, the member state of the plant statesignal 47 indicates "reactor level=L7" and "jet pump dischargedecreasing". Where the member state is present in two or more, themember state higher in importance is subjected to retrieval. Animportance of the member state is specified beforehand. In thisembodiment, "reactor level=L7" is more important and hence is subjectedto retrieval. "Reactor level=L7" is so given as a consequence of thereactor level having ascended, therefore "reactor level ascending" isretrieved from the consequence division of the cause-consequence database 22, and "void increase" and "feed water flow increase" which areitems of the cause division corresponding thereto are added to the plantstate signal 47. The consequence division of the cause-consequence database 22 is again retrieved. However, nothing will be retrieved. Next, adecision is made on the retrieved consequence. Since nothing can beretrieved in this case, the cause lister portion 33 outputs plant statesignals 48A and 48B to which "void increase" and "feed water lowincrease" are added as shown in FIG. 22A and FIG. 22B.

The status recognizer portion 31 retrieves items of "void increase" and"feed water flow increase" from the cause division of thecause-consequence data base 22 by inputting the plant state signals 48Aand 48B and obtains "reactor water level rise" which is an item of theconsequence division corresponding thereto. Then, plant state signals49A and 49B with the above added thereto are outputted. The plant statesignals 49A and 49B are inputted to the predictor portion 34 (FIG. 12).

A transition of the plant state when the void increases and the feedwater flow increases from a combination of "cause" and "consequence"enclosed in the cause-consequence data base 22 can be forecasted byusing the predictor portion 34. The predictor portion 34 retrieves amember state in the plant state signals 49A and 49B for which a changetime is not calculated and calculates the time in which each retrievedmember state changes until there is no member state to be retrieved. Thetime in which the retrieved member state changes refers to a timerequired for the member state to change from the current level to thenext level (the next level being L7 to the current level L6 in thereactor level). Next, whether or not the change time thus obtained isminimum will be decided. A change time for "reactor water levelincrease" to each of "void increase" and "feed water flow increase" ofthe plant state signals 49A and 49B is obtained according to thecalculating method (time calculating method) shown in the predictor database 23 of FIG. 3. Then, each member state after the minimum change timethus obtained passes is calculated according to a technique (statecalculating method) of the predictor data base 23. The predictor portion34 outputs plant state signals 50A, 50B with a new plant state signaladded which is shown in FIG. 23A and FIG. 23B. A change of thephenomenon arising according to "cause" specified by the cause listerportion 33 (or "consequence" retrieved by the status recognizer portion31 of the cause decision division 32), which will be brought as timepasses can be obtained by the predictor portion 34. A decision onwhether or not the "cause" estimated by the cause lister 33 is a truecause will thus be facilitated, even if an abnormality occurs with adynamic process amount of the boiling water reactor plant. In otherwords, the true cause which brings a plant data indicating theabnormality measured actually at the boiling water reactor can beobtained easily thereby.

The checker portion 35 shown in FIG. 13 which has inputted the plantstate signals 50A and 50B ensures that the plant state signal producedin consequence does not include a member state which is not present inthe plant state actually produced and for which the cause is notestimated by the cause lister portion 33 itself. The confirmed plantstate signal is outputted as it is, however, that of having produced amember state which is not present in the actual plant state but taken inby the data translator portion 30 as a consequence is regarded improperas a cause and hence is not outputted. In this embodiment, the statesignals 50A and 50B of FIG. 23A and FIG. 23B are not contradictory andoutputted as they are from the non-contradiction checker portion 35.

The plant state signals 50A, 50B outputted from the checker portion 35are inputted to the recursion controller portion 36. The recursioncontroller portion 36 compares the plant state signals 50A and 50B whichare outputs of the checker portion 35 with the plant state signal 47outputted to the cause decision division 32. Where either one memberstate of the plant state signals 50A and 50B coincides with the plantstate signal 47, the recursion controller portion 36 will not function.In this case, the plant state signals 50A and 50B are transferred to thedecider portion 37. In this embodiment, a member state "jet pump flowdecrease" is included in the plant state signal 47 but not included inboth the plant state signals 50A and 50B. The recursion controllerportion 36 therefore calls recursively the cause decision division 32for which the plant state signals 50A and 50B work as inputs. Namely,the processing from the cause lister portion 33 to the checker portion35 is rerun. The plant state signals 50A and 50B are inputted to thecause lister portion 33. The cause lister portion 33 retrieves theconsequence division of the cause-consequence data base 22 with themember states "void increase" and "feed water flow increase" of theplant state signals 50A and 50B as "consequence", thereby obtaining"cause" corresponding thereto. Seizure of primary loop recirculationpump" indicated by 51A in FIG. 24A is retrieved for the former; "feedwater control system failure" indicated by 51B in FIG. 24B is retrievedfor the latter. Plant state signals 51A and 51B with these member statesadded to the plant state signals 50A and 50B are outputted from thecause lister portion 33. The The status recognizer portion 31 retrievesall "consequences" coming from the "cause" of member states of the plantstate signals 51A and 51B from the cause-consequence data base 22. "Jetpump flow decrease" is retrieved for "seizure of primary looprecirculation pump" of the plant state signal 51A in addition to "voidincrease", and "flow mismatch" is retrieved for "feed water controlsystem failure" of the plant state signal 51B in addition to "feed waterflow increase". Each plant state signal 52A and 52B (FIG. 24A and FIG.24B) to which these member states are added are outputted from thestatus recognizer portion 31 and inputted to the predictor portion 34.No change will be brought on the plant state signal from forecasting thetransition of the plant state signals 52A and 52B as mentioned by thepredictor portion 34, and hence they are inputting straight to thechecker portion 35. The are also decided as not contradictory here andoutputted straight accordingly.

The plant state signals 52A and 52B outputted from the checker portion35 are inputted to the recursion controller portion 36. As describedhereinabove, the recursion controller portion 36 compares the plantstate signal 47 with the plant state signals 52A and 52B. The two memberstates reactor level L7" and "jet pump flow decrease" of the plant statesignal 47 are also present in the plant state signal 52A. The recursioncontroller portion 36 therefore does not carry out a recursive call ofthe cause decision division 32 and outputs the plant state signals 52Aand 52B to the decider portion 37.

The decider portion 37 compares the plant state signals 52A and 52Bshown in FIG. 24A and FIG. 24B respectively with the plant state signal47 of FIG. 21 which indicates an actual plant state of the boiling waterreactor plant.

Where "seizure of primary loop recirculation pump" is the cause, theplant state signal 52A coincides with the plant state signal 47.However, where "feed water control system failure" is the cause, theplant state signal 52B does not coincide with the plant state signal 47.Therefore, "seizure of primary loop recirculation pump" is decided asthe cause, and the plant state signal 52A shown in FIG. 24A is outputtedas a plant state signal 53 which is an output of the cause decisiondivision 32. The processing on the cause decision division 32 is thusclosed.

Since there exists the recursion controller portion 36, it can easily bedecided whether or not the plant state resulting from the "cause"estimated according to this embodiment will be identified with a plantstate indicating abnormality occurring at the boiling water reactorplant. Therefore, a true "cause" for the plant state indicatingabnormality can be obtained simply and precisely.

A feature to decide whether or not a recursive call will have to becarried out through comparing a member state of the first plant statesignal inputted to the cause decision division 32 with a member state ofthe second plant state signal outputted from the checker portion 35 canbe placed on the front stage of the recursion controller portion 36separately from the recursion controller portion 36. In case the memberstate of the second plant state signal coincides with a part of themember state of the first plant state signal and a new cause is notretrieved at the cause lister portion 22 after recursive call, it istaken that an abnormal phenomenon due to a different cause has occurredin two or more (multiple phenomenon). In such case, a cause to producethe member state of the first plant state signal after the member stateof the second plant state signal is eliminated from that of the firstplant state signal is obtained at the cause decision division 32similarly as mentioned hereinabove.

The plant state signal 53 (the plant state signal 52A essentially thistime) which is an output of the decider portion 37 of the cause decisiondivision 32 is inputted to the countermeasure lister portion 39 of theoptimal operation determination division 38. The countermeasure listerportion 39 retrieves the condition division of the countermeasure database 24 for each member state of the plant state signal 52A and obtainsan operation plane corresponding to the item of the condition division.In this embodiment, the corresponding item is not present in thecondition division of the countermeasure data base 24, as "reactor levelL7". Therefore, there is no concrete operation plan in this case, and aplant state signal 54 with the operation plan "nothing operated" addedto the plant state signal 53 is outputted from the countermeasure listerportion 39.

Next, the predictor portion 34 will function from inputting the plantstate signal 54. The predictor portion 34 outputs a plant state signal55 to which the change time of each member state of the plant statesignal 54 and each member state after the minimum change time passes areadded. Concretely, a state changing at the minimum change time is thereactor level, and a member state after passing the minimum time is the"reactor water level rise, L8". The plant state signal 55 to which themember state is added is outputted from the predictor portion 34.

The plant state signal 55 is inputted to the status recognition portion31. The status recognition portion 31 retrieves a consequence "turbinetrip" to the member state "reactor level rise, L8" which is added newlyaccording to the cause-consequence data base 22. The state graspdivision 31 further retrieves consequences "scram: switch electric busand "reactor pressure rise" to the cause of retrieved member state"turbine trip". A plant state signal 56 (FIG. 25) to which these newmember states are added is the output of the status recognition portion31.

The plant state signal 56 is inputted to the recursion controllerportion 40. The portion 40 has a means to compare the plant state signalinputted to the countermeasure lister portion 39 with the plant statesignal outputted therefrom, thereby deciding whether or not a newoperation plan is added to the latter signal. Upon deciding that a newoperation plan has been added, the recursion controller portion callsthe optimal operation determination division 38 recursively, however, ifthe decision comes contrary thereto, then the recursive call will not becarried out. The operation plan "no operation carried out" is given inthis embodiment, therefore a recursive call is made to the optimaloperation determination division 38, and a processing is again effectedon the countermeasure lister portion 39, the predictor portion 34 andthe status recognition portion 31, each. The plant state signal 56 whichis an output of the status recognition portion 31 is inputted to thecountermeasure lister portion 39.

The countermeasure lister portion 39 inputs the plant state signal 56and retrieves an operation plan to cope with the member state of thissignal from the countermeasure data base 24. In this embodiment, anoperation "motor driven feed water pump trip" corresponding to "reactorlevel rise, L8" is retrieved, and further "no operation carried out" isenumerated as an operation plan. Plant state signals to which theseoperation plans are added, i.e. plant state signals 57A and 57B shown inFIG. 26A and FIG. 26B respectively are inputted to the predictor portion34. A transition of the plant state when each operation is carried outis forecasted by the predictor portion 34 as mentioned above. Namely,consequences of "reactor pressure rise, high" and "reactor levelsuddenly decreasing, L4" will be forecasted after the minimum changetime passes further from the minimum change time obtained through theprevious processing of the predictor portion 34 by executing "motordriven feed water pump trip" of the plant state signal 57A. "Reactorpressure rise, high" and "reactor water level fall, L6" will also beforecasted in the case of "no operation carried out". Plant statesignals 58A and 58B to which these member states are added are inputtedto the status recognition portion 31 from the predictor portion 34.

The status recognition portion 31 retrieves a "consequence"corresponding to each member state from the cause-consequence data base22. Namely, for the plant state signal 58A having an operation plan"motor driven feed water pump trip", a consequence "bypass valve open"to the cause "reactor pressure high", a consequence "reactor water levellow" to the cause "motor driven feed water pump trip", a consequence"void decrease" to the cause "scram (after a given time passes)" (sincethe minimum change time passed two times after scram), and a consequence"reactor level fall" to the cause "void decrease" are retrieved. A plantstate signal 59A of FIG. 26A to which these retrieved consequences areadded is obtained through processing of the status recognition portion31. Then, for the plant state signal 58B having an operation plan "nooperation carried out", the consequence "bypass valve open" to the cause"reactor pressure high", the consequence "void decrease" to the cause"scram (after a given time passed)", and the consequence "reactor levelfall" to the cause "void decrease" are retrieved. A plant state signal59B of FIG. 26B to which these retrieved consequences are added isobtained through processing of the status recognition portion 31.

The plant state signals 59A and 59B are inputted to the recursioncontroller portion 40. The portion 40 determines whether or not theoptimal operation determination division 38 will have to be calledrecursively again according to whether or not the above-mentioned newoperation plan has been added in the processing of the countermeasurelister portion 39 after recursive call. Since "motor driven feed waterpump trip" is added as a new operation plan this time, a recursive callof the optimal operation determination division 38 is rerun. The plantstate signals 59A and 59B are inputted to the countermeasure listerportion 39. However, the portion 39 does not add an operation plan newlyto those of plant state signals 59A and 59B. Next, the predictor portion34 inputs the plant state signals 59A and 59B outputted from thecountermeasure lister portion 39 to forecast a state of each memberstate of the plant state signals after the minimum change time passes.Namely, for the plant state signal 59A having an operation plan "motordriven feed water pump trip", the reactor level is changed to "L2" andthe reactor pressure is changed to "descending". Then, for the plantstate signal 59B having an operation plan "no operation carried out",the reactor level is changed to "L4" and the reactor pressure is changedto "descending". The predictor portion 34 outputs plant state signals60A and 60B shown in FIG. 27A and FIG. 27B for each operation plan.

The plant state signals 60A and 60B are inputted to the recursioncontroller portion 40. Since nothing is added newly at thecountermeasure lister portion 39, a recursive call is not carried outthis time. Therefore, the plant state signals 60A and 60B are inputtedto the selected portion 41. The selector portion 41 selects either oneof the plant state signals 60A and 60B as an optimal operation. Namely,"reactor level L2" will result from carrying out "motor driven feedwater pump trip" of the plant state signal 60A, and "reactor level L4"will result from carrying out "no operation carried out". "No operationcarried out" will be most pertinent to "seizure of primary looprecirculation pump" this time, thereby complying with the operationcondition of the boiling water reactor plant, "not to drop reactorlevel". Therefore, the plant state signal 60B of FIG. 27B is outputtedfrom the optimal operation determination division.

The predictor portion 34 is provided at the optimal operationdetermination division 38 in this embodiment, therefore when anoperation (retrieved by the countermeasure lister portion 39) todissolve the true cause of an abnormal state obtained at the causedecision division 32 is carried out, the future plant state which willbe so obtained through carrying out the operation can be forecasted. Inother words, the value of a dynamic process amount in the future can beforecasted. Moreover, the recursion controller portion 40 is alsoprovided at the optimal operation determination division 38, thereforean optimal operation can easily be determined in consideration of thefuture plant state obtained at the predictor portion 34. According tothis embodiment, an abnormal state occurring currently at the boilingwater reactor plant can be dissolved easily, and an optimal operationhigh in safety can be selected, too. Further in the embodiment availableby combining the cause decision division 32 having the predictor portion34 and the recursion controller portion 36 with the optimal operationdetermination division 38 having the predictor portion 34 and therecursion controller portion 40, since the true cause of an abnormalstate can be precisely recognized, the operation obtained for dissolvingthe abnormal state might be the best possible one. Furthermore, acorrect cause can be found thereby, therefore whether or not the plantmust be repaired immediately can be decided efficiently, a spot torepair can be detected beforehand for necessary repair, if any, and therepair after shutdown of the plant can be effected within a short periodof time.

The plant state signal 60B outputted from the selector portion 41 of theoptimal operation determination division 38 is inputted to the detailsearcher portion 42. In this embodiment, the optimal operation being "nooperation carried out", the detail searcher portion 42 does notfunction. The detail searcher portion 42 outputs the plant state signal60B as an output (a plant state signal 61) of the detail searcherportion 42. For example, in case "motor driven feed water pump trip" ofthe plant state signal 60A is carried out and thus a high pressureinjection system is operated by "reactor level L2" of the plant statesignal 60A, a detail operating method (FIG. 5) of the high pressureinjection system is picked out of the detail data base 25, and a plantstate signal to which the above is added is outputted from the detailsearcher portion 42. And where there is observed an offense fromcarrying out a close confirmation on the operation limit, a plant statesignal to which "high pressure injection system cannot be used" is addedis outputted, the output is then transferred to the optimal operationdetermination division 38 to rerun the above-mentioned processing of theoptimal operation determination division 38, and a planning of theoperation is again requested.

The example searcher portion 43 shown in FIG. 18 is actuated frominputting the plant state signal 61. The example searcher portion 43retrieves a case analogous to the plant state signal 61 from the exampledata base 26 which encloses practical cases as shown in FIG. 6. In thisEmbodiment, Case 1 representing "seizure of primary loop recirculationpump" shown in FIG. 6 is retrieved, and the contents are added to theplant state signal 61 to develop to a plant state signal 62, which isoutputted from the example searcher portion 43.

The plant state signal 62 is inputted to the guidance implementationportion 44 shown in FIG. 19. The guidance implementation portion 44outputs the plant state signal 60B shown in FIG. 27B through convertingit into a CRT display output (into a character code for CRT, forexample). In this case, the detail operating method and the contents ofthe analogous case are converted likewise. When converting the plantstate signal 60B into the CRT display output, the guidanceimplementation portion 44 outputs that for CRT display which indicatesthe member state representing a cause and also the member staterepresenting contents of the operation to cope therewith. For example,words (cause) and (operation contents) are added after the correspondingmember states as: "seizure of primary loop recirculation pump (cause)"and "no operation carried out (operation contents)".

An output (plant state signal 60B) of the guidance implementationportion 44 is transferred to CRT 21 to display thereon. Observing theoperation contents displayed on CRT 21, an operator of the boiling waterreactor plant will operate an object equipment of the boiling waterreactor plant on a control panel accordingly. The operation contents ofthis embodiment being "no operation carried out", a concrete operationwill not be made for the boiling water reactor plant. To say reversely,an operation "no operation carried out" is performed for the boilingwater reactor plant. From carrying out such operation, a void decreases,the reactor level 17 descends to the level L4, the bypass valve opensautomatically, and thus the reactor pressure drops to a safe state inthe boiling water reactor plant. In case, for example, contents of theplant state signal 60A are determined to be an optimal operation at theselector portion 41, the operator will operate the control panel 20 soas to trip a motor driven feed water pump according to the operationcontents displayed on CRT 21. The command is given to feed water pumps10A and 10B in operation from the control panel 20. Thus the feed waterpumps 10A and 10B come to shutdown.

According to this embodiment, phenomena arising on the plant are alldisplayed on CRT when an actual operation is carried out based on thedisplayed operation contents, therefore a progress of the operation canbe supervised by confirming the change of an actual state of the plant.Further, when "cause decision" and "operation determination" are made byutilizing the cause-consequence data base 22, a use of the predictorportion 34 may ensure a safe operation of the boiling water reactorplant (safety being ensured even from the motor driven feed water pumpin trip) against an abnormal phenomenon which is not conceivableactually like "seizure of primary loop recirculation pump", thusobtaining an optimal operation high in safety.

When a guidance for such operating method as is high in safety againstan abnormal phenomenon actually not conceivable for occurrence will haveto be secured on an operation guide apparatus merely utilizing CCT and atechnique of knowledge engineering (not including the predictor portionand the recursion controller portion unlike this embodiment), alarge-scale data base must be provided, and labor will be required muchfor rules for the guidance implementation and maintenance. Amaterialization by the technique may involve difficulty, accordingly.Namely, a method to utilize CCT requires a vast amount of CCT todifficulty of implementation and maintenance. And in case the techniqueof knowledge engineering is utilized, the data runs vast inevitably involume from the requirements that a data representing cause andconsequence must be prepared to cover the case wherein the measuredresult to indicate the state of a plant is present plurally and that adata limited for the range of application must be prepared inconsideration of forecasting a transition (or forecasting a change indynamic process amount) of the plate beforehand since it cannot beforecasted.

According to a technique of this embodiment, operators are kept fromtroubles to improve the guidance operation, carry out such erroneousoperation as will reduce an effect of the guidance operation, or takemuch time to cope with a load fluctuation when the plant is activated.

Then, a guidance coping at all times with a renewed situation can beprovided to operators by rerunning the above processing through ageneration of a new alarm, another request by the operator, or aninterruption of an internal clock of the operation guide apparatus.

When the embodiment is put into practice, the plant data can be inputtedat every member states at the point in time when the status recognitionportion 31 is actuated, and the cause division of the cause-consequencedata base 22 and the plant state signal are compared with each other.

When a plurality of plant states are obtained on the data transitionportion 30, other technique to select such value as is not preferablefor the plant than a majority decision can be used for logical decisionto narrow down the states to one.

In the cause decision division 32, causes which are not contradictoryeach other will be outputted as a plural cause instead of concluding thecause to one only, and the ensuing processing can be done for each ofthem.

In the optimal operation determination division 38, the operation willnot be determined to one only, those which meet the object of operationwill be outputted accordingly, and the operator may have an option toselect suitably from among them. Then, the processing can be cut tooutputting at the point in time when those of meeting the object ofoperation are found more than the number set initially instead ofobtaining an optimal operation.

The same one as the cause-consequence data base 22 will be used for thecountermeasure data base 24, which can be identified by marking upproperly for the contents.

The detail portion 42 and the example searcher portion 43 may beactuated upon indication of the operator. Then, a retrieval of analogouscases may be processed antecedently, or both may be processedconcurrently, or either one only may be processed.

The predictor portion 34 can interpret an expression on the predictiondata base 23 directly to execution, or it can operate for calculation bycalling a subroutine for which information is stored on the predictiondata base 23. Then, a table search can be done directly by the forecastfeature or by a private subroutine with a similar technique.

For control of the cause decision division 32 and the optimal operationdetermination division 38, a similar processing can be implemented on asoftware by means of a stack instead of using a recursive call feature,or a function to realize the cause decision division 32 and the optimaloperation determination division 38 is built on a hardware, which willbe connected in series therefor by the number taken enough.

According to the embodiment given in FIG. 1, a large-scale data base isnot required, which may facilitate implementation and maintenance. Then,since contents of the data base are independent at every units ofconfiguration as shown in FIG. 2 to FIG. 6, in an extreme case, if any,where a phenomenon which is not included in the data base is produced, atrained operator will cope with such phenomenon by inputting the featureonly to the data base, and thus a function of the operation guideapparatus can be amplified.

This invention can be applied to a pressurized water reactor plant, afast breeder reactor plant and a thermal power plant, too.

According to this invention, a true cause of an abnormal state of theplant can be recognized.

What is claimed is:
 1. A plant operating method comprising the stepsof:detecting plant data from a plant; identifying the actual status ofall members of the plant indicating an abnormality of the plant from thedetected plant data; estimating a cause of an occurrence of theabnormality in accordance with the actual status of the plant members;predicting the status of all plant members after a given period of timehas passed in accordance with the estimated cause; determining whetheror not the actual status of the plant members are present in thepredicted status of the plant members; repeatedly carrying out the stepof estimating a cause of occurrence of the abnormality and predictingthe status of all plant members in accordance therewith when it isdetermined that the actual status of all the plant members are notpresent in the predicted status of the plant members detected until theactual status of all the plant members come to exist in the predictedstatus of the plant members; selecting a plant operation plan forovercoming the estimated cause of occurrence of the abnormality when theactual status of all of the plant members are present in the status ofthe predicted plant members; and operating the plant according to theselected operation plan.
 2. The plant operating method according toclaim 1, wherein the step of estimating the cause of occurrence of theabnormality is based upon data providing a cause and effectrelationship.
 3. The plant operating method as defined in claim 1,wherein the step of selecting an operation plan for overcoming theestimated cause of the abnormality includes predicting the status of theplant members when the selected operation is put into practice for agiven period of time, determining whether or not the selected operationplan should be selected, and repeatedly carrying out selection of anoperation plan to overcome an occurrence of the predicted status of theplant members in accordance with the selected operation plan until nooperation plan is selected, and thereafter selecting an operating planwhich satisfies operating conditions for the plant as the selectedoperation plan from among the operation plans thus obtained.
 4. Theplant operating method according to claim 3, wherein the step ofselecting an operation plan includes retrieving data indicating theoperation plan corresponding to the predicted status of the plantmembers.
 5. The plant operating method according to claim 3, includingthe step of determining the status of the plant members arising as aconsequence of the predicted status of the plant members.
 6. The plantoperating method according to claim 5, wherein the status of the plantmembers arising as a consequence of the predicted status of the plantmembers is obtained by retrieving data providing a cause and effectrelationship.
 7. The plant operating method according to claim 1 or 3,further comprising the steps of obtaining a detail procedure for theselected operating plan and determining whether the detail procedure iscontrary to the limitations on the plant operation, and carrying out theselected operation plan when the detail procedure is not contrary tolimitations on the plant operation, and selecting another operation planfor overcoming the estimated cause of the abnormality when the detailprocedure is contrary to the limitations on the plant operation. .Iadd.8. An operating method comprising the steps of:(1) inputting data of asystem to be operated; (2) identifying the actual status of all membersof the system indicating an abnormality of the system from the inputteddata; (3) estimating at least one cause of an occurrence of theabnormality in accordance with the actual status of the members; (4)predicting the status of all members after a given period of time haspassed in accordance with the estimated cause; (5) determining whetheror not the actual status of the members are present in the predictedstatus of the members; (6) repeatedly carrying out the step ofestimating at least one cause of occurrence of the abnormality andpredicting the status of all members in accordance therewith when it isdetermined that the actual status of all members are not present in thepredicted status of the members until the actual status of all memberscome to exist in the predicted status of the members; (7) selecting anoperation plan for overcoming the estimated cause of occurrence of theabnormality when the actual status of all of the members are present inthe status of the predicted members; and (8) operating the systemaccording to the selected operation plan. .Iaddend. .Iadd.9. Anoperating method according to claim 8, wherein the step of estimatingthe cause of occurrence of the abnormality is based upon data providinga cause and consequence relationship. .Iaddend. .Iadd.10. An operatingmethod according to claim 8, wherein the step of selecting an operationplan for overcoming the estimated cause of the abnormality includes thesteps of: (1) predicting the status of the members when the selectedoperation is put into practice for a given period of time; (2)determining whether or not the selected operation plan should beselected; (3) repeatedly carrying out selection of an operation plan toovercome an occurrence of the predicted status of the members inaccordance with the selected operation plan until no operation plan isselected; and thereafter (4) selecting an operation plan which satisfiesoperating conditions for the system as the selected operation plan fromamong the operation plans thus obtained. .Iaddend. .Iadd.11. Anoperating method according to claim 10, wherein the step of selecting anoperation plan includes the step of retrieving data indicating theoperation plan corresponding to the predicted status of the members..Iaddend. .Iadd.12. An operating method according to claim 10, furthercomprising the step of determining the status of the members arising asa consequence of the predicted status of the members. .Iaddend..Iadd.13. An operating method according to claim 12, wherein the statusof the members arising as a consequence of the predicted status of themembers is obtained by retrieving data providing a cause and consequencerelationship. .Iaddend. .Iadd.14. A method according to claim 8 or 10,further comprising the steps of: (1) obtaining a detail procedure forthe selected operation plan; (2) determining whether the detailprocedure is contrary to the limitations on the operation; (3) carryingout the selected operation plan when the detail procedure is notcontrary to limitations on the operation; and (4) selecting anotheroperation plan for overcoming the estimated cause of the abnormalitywhen the detail procedure is contrary to the limitations on theoperation. .Iaddend. .Iadd.15. A method comprising the steps of: (1)inputting data of an object; (2) identifying the actual status of allmembers of the object indicating an abnormality of the object from theinputted data; (3) estimating at least one cause of an occurrence of theabnormality in accordance with the actual status of the members; (4)predicting the status of all members after a given period of time haspassed in accordance with the estimated cause; (5) determining whetheror not the actual status of the members are present in the predictedstatus of the members; (6) repeatedly carrying out the step ofestimating at least one cause of occurrence of the abnormality andpredicting the status of all members in accordance therewith when it isdetermined that the actual status of all members are not present in thepredicted status of the members detected until the actual status of allmembers come to exist in the predicted status of the members; and (7)selecting an operation plan for overcoming the estimated cause ofoccurrence of the abnormality when the actual status of all of themembers are present in the status of the predicted members. .Iaddend..Iadd.16. A method according to claim 15, wherein the cause ofoccurrence of the abnormality is based upon data providing a cause andconsequence relationship. .Iaddend. .Iadd.17. A method according toclaim 15, wherein the step of selecting an operation plan for overcomingthe estimated cause of the abnormality includes the steps of: (1)predicting the status of the members when the selected operation plan isput into practice for a given period of time, (2) determining whether ornot the selected operation plan should be selected, (3) repeatedlycarrying out selection of an operation plan to overcome an occurrence ofthe predicted status of the members in accordance with the selectedoperation plan until no operation plan is selected, and thereafter (4)selecting an operating plan which satisfies operating conditions for theobject as the selected operation plan from among the operation plansthus obtained. .Iaddend. .Iadd.18. A method according to claim 17,wherein the step of selecting an operation plan includes the step ofretrieving data indicating the operation plan corresponding to thepredicted status of the members. .Iaddend. .Iadd.19. A method accordingto claim 17, further comprising step of determining the status of themembers arising as a consequence of the predicted status of the members..Iaddend. .Iadd.20. A method according to claim 19, wherein the statusof the members arising as a consequence of the predicted status of themembers is obtained by retrieving data providing a cause and consequencerelationship. .Iaddend. .Iadd.21. A method according to claim 15 or 17,further comprising the steps of: (1) obtaining a detail procedure forthe selected operation plan; (2) determining whether the detailprocedure is contrary to the limitations on the operation; and (3)selecting another operation plan for overcoming the estimated cause ofthe abnormality when the detail procedure is contrary to the limitationson the operation. .Iaddend. .Iadd.22. An apparatus including a computercomprising:(1) a memory for storing data bases including(a) a data baserecording relations of causes and consequences, (b) a data baserecording information to predict transitional behavior of an object, and(c) a data base recording operation plans; and (2) means for carryingout a processing program to make a guidance consultation to overcome acause of abnormality of the object including(a) means for inputting dataof the object, (b) means responsive to the inputting means foridentifying the actual status of all members of the object indicating anabnormality of the object from the inputted data, (c) means responsiveto the identifying means for estimating a cause of an occurrence of theabnormality in accordance with the actual status of the members, (d)means responsive to the estimating means for predicting the status ofall members after a given period of time has passed in accordance withthe estimated cause, (e) means responsive to the predicting means fordetermining whether or not the actual status of the members are presentin the predicted status of the members, (f) means responsive to thedetermining means for repeatedly carrying out the estimating of a causeof occurrence of the abnormality and predicting the status of allmembers in accordance therewith when it is determined that the actualstatus of all members are not present in the predicted status of themembers detected until the actual status of all members come to exist inthe predicted status of the member, and (g) means responsive to therepeatedly carrying out means for selecting an operation plan forovercoming the estimated cause of occurrence of the abnormality when theactual status of all of the members are present in the status of thepredicted members. .Iaddend. .Iadd.23. An apparatus according to claim22, wherein the means for estimating the cause of occurrence of theabnormality are based upon data providing a cause and consequencerelationship. .Iaddend. .Iadd.24. An apparatus according to claim 22,wherein the means for selecting an operation plan for overcoming theestimated cause of the abnormality includes:(1) means for listing atleast one operation plan; (2) means responsive to the listing means forpredicting the status of the members when a selected operation plan isput into practice for a given period of time; (3) means responsive tothe predicting means for determining whether or not the selectedoperation plan should be selected; (4) means responsive to thedetermining means for repeatedly carrying out selection of anotheroperation plan to overcome an occurrence of the predicted status of themembers in accordance with the selected operation plan until nooperation plan is selected; and thereafter (5) means responsive to therepeatedly carrying out means for selecting an operation plan whichsatisfies operating conditions for the object as the selected operationplan from among the operation plans thus obtained. .Iaddend. .Iadd.25.An apparatus according to claim 24, wherein the means for selecting anoperation plan further includes means for retrieving data indicating theoperation plan corresponding to the predicted status of the members..Iaddend. .Iadd.26. An apparatus according to claim 24, furthercomprising means for determining the status of the members arising as aconsequence of the predicted status of the members. .Iaddend. .Iadd.27.An apparatus according to claim 26, wherein the status of the membersarising as a consequence of the predicted status of the members isobtained by retrieving data providing a cause and consequencerelationship. .Iaddend. .Iadd.28. An apparatus according to claim 22 or24, further comprising:(1) means responsive to the selecting means forobtaining a detailed procedure for the selected operation plan; (2)means responsive to the detail means for determining whether thedetailed procedure is contrary to the limitations on the operation; and(3) means responsive to the determining means for selecting anotheroperation plan for overcoming the estimated cause of the abnormalitywhen the detailed procedure is contrary to the limitations on theoperation. .Iaddend. .Iadd.29. An apparatus including a computercomprising: (1) memory means for storing information forming a knowledgebase including(a) data as facts expressed as at least one identifierportion indicative of a state of an object and a corresponding valueportion, and (b) rules including IF parts and corresponding THEN parts,each of the IF parts and corresponding THEN parts including anidentifier portion and a corresponding value; and (2) means for carryingout a processing program including interpretation of the knowledge basefor guidance including(a) means for searching the knowledge base inaccordance with a predetermined fact for comparing facts and rules so asto obtain at least one of an IF part or THEN part of a rule as a resultof the comparison, (b) means responsive to the searching means forutilizing the comparison result as a new fact for searching of theknowledge base by the searching means, (c) means responsive to nocomparison result from the searching means for terminating the search ofthe knowledge base, and (d) means responsive to termination of thesearch of the knowledge base by the terminating means for outputting aresult of carrying out the processing program. .Iaddend. .Iadd.30. Anapparatus according to claim 29, wherein the means for carrying out aprocessing program further includes:(1) means for inputting data of theobject; (2) means responsive to the storing means for utilizing theactual status of all the members of the object indicating a state of theobject as different facts, each having an identifier portion indicativeof the state of the object and a corresponding value; (3) meansresponsive to the utilizing means for searching the knowledge base toobtain an IF part of a rule in accordance with a predetermined fact whenutilizing the predetermined fact as a THEN part of the rule; (4) meansresponsive to the searching means for predicting the status of allmembers after a given period of time has passed in accordance with theIF part obtained as a new fact; and (5) means responsive to thepredicting means for searching the knowledge base to determine whetheror not the actual status of the members are present in the predictingstatus of the members. .Iaddend. .Iadd.31. An apparatus according toclaim 30, further comprising means for selecting an operation planincluding:(1) means for listing at least one operation plan; (2) meansresponsive to the listing means for predicting the status of the memberswhen the selected operation plan is put into practice for a given periodof time; (3) means responsive to the predicting means for determiningwhether or not the selected operation plan should be selected; (4) meansresponsive to the determining means for repeatedly carrying outselection of another operation plane in accordance with the selectedoperation plan until no operation plan is selected; and thereafter (5)means responsive to the repeatedly carrying out means for selecting anoperation plan from among the operation plans thus obtained. .Iaddend..Iadd.32. An apparatus according to claim 31, wherein the means ofselecting an operation plan includes means for retrieving dataindicating the operation plan corresponding to the predicted status ofthe members. .Iaddend. .Iadd.33. An apparatus according to claim 31,further comprising:(1) means responsive to the selecting means forobtaining a detailed procedure for the selected operation plan; (2)means responsive to the detail means for determining whether thedetailed procedure is contrary to the limitations on the operation; and(3) means responsive to the determining means for selecting anotheroperation plan when the detailed procedure is contrary to thelimitations on the operation plan. .Iaddend. .Iadd.34. An apparatusaccording to claim 31, further comprising means for determining thestatus of the members arising as a consequence of the predicted statusof the members. .Iaddend. .Iadd.35. An apparatus according to claim 34,wherein the status of the status of the members arising as a consequenceof the predicted status of the members is obtained by retrieving dataproviding a cause and consequence relationship. .Iaddend. .Iadd.36. Amethod comprising the steps of:(1) storing a data base forming aknowledge base including(a) data as facts expressed as at least oneidentifier portion indicative of the state of an object and acorresponding value portion, and (b) rules including IF parts andcorresponding THEN parts, each of the IF parts and corresponding THENparts including an identifier portion and a corresponding value; and (2)carrying out a processing program including interpretation of theknowledge base for guidance including(a) searching the knowledge base inaccordance with a predetermined fact for comparing facts and rules so asto obtain at least one of an IF part or THEN part of a rule as a resultof the comparison, (b) utilizing the comparison result as a new fact forsearching the knowledge base, (c) terminating the search of theknowledge base when no comparison result is obtained, and (d) outputtinga result of carrying out the processing program in response totermination of the search of the knowledge base. .Iaddend. .Iadd.37. Amethod according to claim 36, further comprising the steps of:(1)inputting data of the object, (2) utilizing the actual status of allmembers of the object indicating a state of the object as differentfacts, each having an identifier portion indicative of the state of theobject and a corresponding value, (3) searching the knowledge base toobtain an IF part of a rule in accordance with a selected fact whenutilizing the selected fact as a THEN part of a rule, (4) predicting thestatus of all members after a given period of time has passed inaccordance with the IF part obtained as a new fact, and (5) searchingthe knowledge base to determine whether or not the actual status of themembers are present in the predicted status of the members. .Iaddend..Iadd.38. A method according to claim 37, further comprising the step ofselecting an operation plan including the steps of (1) predicting thestatus of the plant members when the selected operation plan is put intopractice for a given period of time, (2) determining whether or not theselected operation plan should be selected, (3) repeatedly carrying outselection of an operation plan in accordance with the selected operationplan until no operation plan is selected, and thereafter (4) selectingan operation plan from among the operation plans thus obtained..Iaddend. .Iadd.39. A method according to claim 38, wherein the step ofselecting an operation plan includes the step of retrieving dataindicating the operation plan corresponding to the predicted status ofthe members. .Iaddend. .Iadd.40. A method according to claim 38, furthercomprising the steps of:(1) obtaining a detail procedure for theselected operation plan, (2) determining whether the detail procedure iscontrary to the limitations on the operation, and (3) selecting anotheroperation plan when the detail procedure is contrary to the limitationson the operation. .Iaddend. .Iadd.41. A method according to claim 38,further comprising the step of determining the status of the membersarising as a consequence of the predicted status of the members..Iaddend. .Iadd.42. A method according to claim 41, wherein the statusof the members arising as a consequence of the predicted status of themembers is obtained by retrieving data providing a cause and consequencerelationship. .Iaddend. .Iadd.43. An apparatus including a computercomprising:(1) memory means for storing data forming a knowledge baseincluding(a) data as facts expressed as at least one identifier portionindicative of a state of an object and a corresponding portion, and (b)rules including IF parts and corresponding THEN parts, each of the IFparts and corresponding THEN parts including an identifier portion and acorresponding value; and (2) means for carrying out a processing programfor interpretation of the knowledge base including(a) means forsearching the knowledge baes in accordance with a selected fact forcomparing facts and rules so as to obtain at least one of an IF part orTHEN part of a rule as a result of the comparison, (b) means responsiveto the comparison result of the searching means for terminating thesearch of the knowledge base, and (c) means responsive to theterminating means terminating the search of the knowledge base foroutputting a result of carrying out the processing program. .Iaddend..Iadd.44. An apparatus according to claim 43, wherein the means forcarrying out a processing program further includes(1) means forinputting data of the object, (2) means for utilizing the actual statusof all members of the object indicating an state of the object asdifferent facts, each having an identifier portion indicative of thestate of the object and a corresponding value, and (3) means forsearching the knowledge base to obtain an IF part of a rule inaccordance with a selected fact when utilizing the selected fact as aTHEN part of a rule. .Iaddend. .Iadd.45. An apparatus according to claim44, further comprising means for selecting an operation plan including(1) means for predicting the status of the members when the selectedoperation plan is put into practice for a given period of time, (2)means for determining whether or not the selected operation plan shouldbe selected, (3) means for repeatedly carrying out selection of anoperation plan in accordance with the selected operation plan until nooperation plan is selected, and thereafter (4) means for selecting anoperation plan from among the operation plans thus obtained. .Iaddend..Iadd.46. An apparatus according to claim 45, wherein the means ofselecting an operation plan includes means for retrieving dataindicating the operation plan corresponding to the predicted status ofthe members. .Iaddend. .Iadd.47. An apparatus according to claim 45,further comprising: (1) means for obtaining a detail procedure for theselected operation plan, and (2) means for determining whether thedetail procedure is contrary to the limitations on the operation, andmeans for selecting another operation plan when the detail procedure iscontrary to the limitations on the operation. .Iaddend. .Iadd.48. Anapparatus according to claim 45, further comprising the means ofdetermining the status of the members arising as a consequence of thepredicted status of the members. .Iaddend. .Iadd.49. An apparatusaccording to claim 48, wherein the status of the members arising as aconsequence of the predicted status of the members is obtained byretrieving data providing a cause and consequence relationship..Iaddend. .Iadd.50. A method comprising the steps of:(1) storing a database forming a knowledge base including(a) data as facts expressed as atleast one identifier portion indicative of a state of an object and acorresponding value portion, and (b) rules including IF parts andcorresponding THEN parts, each of the IF parts and corresponding THENparts including an identifier portion and a corresponding value; (2)carrying out a processing program including interpretation of theknowledge base including the steps of(a) searching the knowledge base inaccordance with a selected fact for comparing facts and rules so as toobtain at least one of an IF part or THEN part of a rule as a result ofthe comparison, and (b) terminating the search of the knowledge base inresponse to the comparison result, and outputting a result of carryingout the processing program in response to termination of the search ofthe knowledge base. .Iaddend. .Iadd.51. A method according to claim 50,further comprising the steps of:(1) inputting data of the object (2)utilizing the actual status of all members of the object, indicating astate of the object as different facts, each having an identifierportion indicative of the state of the object and a corresponding value,and (3) searching the knowledge base to obtain an IF part of a rule inaccordance with a selected fact when utilizing the selected fact as aTHEN part of a rule. .Iaddend. .Iadd.52. A method according to claim 50,further comprising the step of selecting an operation plan including thesteps of: (1) predicting the status of the plant members when theselected operation plan is put into practice for a given period of time,(2) determining whether or not the selected operation plan should beselected, (3) repeatedly carrying out selection of an operation plan inaccordance with the selected operation plan until no operation plan isselected, and thereafter (4) selecting an operation plan from among theoperation plans thus obtained. .Iaddend. .Iadd.53. A method according toclaim 52, wherein the step of selecting an operation plan includes thestep of retrieving data indicating the operation plan corresponding tothe predicted status of the members. .Iaddend. .Iadd.54. A methodaccording to claim 52, further comprising the steps of: (1) obtaining adetail procedure for the selected operation plan, and (2) determiningwhether the detail procedure is contrary to the limitations on theoperation, and (3) selecting another operation plan when the detailprocedure is contrary to the limitations on the operation. .Iaddend..Iadd.55. A method according to claim 52, further comprising the step ofdetermining the status of the members arising as a consequence of thepredicted status of the members. .Iaddend. .Iadd.56. A method accordingto claim 55, wherein the status of the members arising as a consequenceof the predicted status of the members is obtained by retrieving dataproviding a cause and consequence relationship. .Iaddend. .Iadd.57. Aprocess comprising the steps of:(1) storing information forming aknowledge base in memory means of a computer including(a) data as factsexpressed to be at least one identifier as a state of an object andcorresponding values, (b) rules including IF parts and correspondingTHEN parts with at least one value for an identifier; (2) storing aprocessing program in memory means of the computer, the processingprogram enabling interpretation of the knowledge base by(a) searchingthe knowledge base for comparing facts and rules, (b) comparing factswith one of IF parts or THEN parts of the rules to obtain at least oneof an IF part or THEN part as a result of the comparison, (c) adding newfacts to the knowledge base as a result of the comparison, (d)terminating the search of the knowledge base, and outputting a result ofcarrying out the processing program; and (3) running the processingprogram for interpretation of the knowledge base. .Iaddend. .Iadd.58. Aprocess according to claim 51, further comprising the steps of:(1)inputting data of the object, (2) utilizing the actual status of allmembers of the object indicating a state of the object as differentfacts, each having an identifier portion indicative of the state of theobject and a corresponding value, (3) searching the knowledge base toobtain an IF part of a rule in accordance with a selected fact whenutilizing the selected fact as a THEN part of a rule, (4) predicting thestatus of all members after a given period of time has passed inaccordance with the IF part obtained as a new fact, and (5) searchingthe knowledge base to determine whether or not the actual status of themembers are present in the predicted status of the members. .Iaddend..Iadd.59. A process according to claim 58, further comprising the stepof selecting an operation plan including the steps of: (1) predictingthe status of the plant members when the selected operation plan is putinto practice for a given period of time, (2) determining whether or notthe selected operation plan should be selected, (3) repeatedly carryingout selection of an operation plant in accordance with the selectedoperation plan until no operation plan is selected, and thereafter (4)selecting an operation plan from among the operation plans thusobtained. .Iaddend. .Iadd.60. A process according to claim 59, whereinthe step of selecting an operation plan includes the step of retrievingdata indicating the operation plan corresponding to the predicted statusof the members. .Iaddend. .Iadd.61. A process according to claim 59,further comprising the steps of: (1) obtaining a detail procedure forthe selected operation plan, and (2) determining whether the detailprocedure is contrary to the limitations on the operation, and (3)selecting another operation plan when the detail procedure is contraryto the limitations on the operation. .Iaddend. .Iadd.62. A processaccording to claim 59, further comprising the step of determining thestatus of the members arising as a consequence of the predicted statusof the members. .Iaddend. .Iadd.63. A process according to claim 62,wherein the status of the members arising as a consequence of thepredicted status of the members is obtained by retrieving data providinga cause and consequence relationship. .Iaddend. .Iadd.64. A processcomprising the steps of:(1) storing information forming a knowledge basein memory means of a computer including(a) data as facts expressed to beat least one identifier as a state of an object and correspondingvalues, (b) rules including IF parts and corresponding THEN parts withat least one value for an identifier; (2) storing a processing programin memory means of the computer, the processing program enablinginterpretation of the knowledge base for guidance by(a) searching theknowledge base for comparing facts and rules, (b) comparing facts withone of IF parts or THEN parts of the rules to obtain at least one of anIF part or THEN part as a result of the comparison, and (c) terminatingthe search of the knowledge base, and outputting a result of carryingout the processing program; and (3) running the processing program forinterpretation of the knowledge base for guidance. .Iaddend. .Iadd.65. Aprocess according to claim 64, further comprising the step of selectingan operation plan including the steps of:(1) predicting the status ofthe plant members when the selected operation plan is put into practicefor a given period of time, (2) determining whether or not the selectedoperation plan should be selected, (3) repeatedly carrying out selectionof an operation plan in accordance with the selected operation planuntil no operation plan is selected, and thereafter (4) selecting anoperation plan from among the operation plans thus obtained. .Iaddend..Iadd.66. A process according to claim 64, further comprising the stepsof:(1) inputting data of the object, (2) utilizing the actual status ofall members of the object indicating a state of the object as differentfacts, each having an identifier portion indicative of the state of theobject and a corresponding value, and (3) searching the knowledge baseto obtain an IF part of a rule in accordance with a selected fact whenutilizing the selected fact as a THEN part of a rule. .Iaddend..Iadd.67. A process according to claim 66 or 65, further comprising thesteps of: (1) obtaining a detail procedure for the selected operationplan, and (2) determining whether the detail procedure is contrary tothe limitations on the operation, and (3) selecting another operationplan when the detail procedure is contrary to the limitations on theoperation. .Iaddend. .Iadd.68. A process according to claim 65, whereinthe step of selecting an operation plan includes the step of retrievingdata indicating the operation plan corresponding to the predicted statusof the members. .Iaddend. .Iadd.69. A process according to claim 65,further comprising the step of determining the status of the membersarising as a consequence of the predicted status of the members..Iaddend. .Iadd.70. A process according to claim 69, wherein the statusof the members arising as a consequence of the predicted status of themembers is obtained by retrieving data providing a cause and consequencerelationship. .Iaddend. .Iadd.71. A method comprising the steps of:(1)storing information including rules relating to status of a system in amemory of a computer, each of the rules having a cause portion and acorresponding consequence portion, (2) inputting data of the status ofthe system, (3) making interferences based upon the inputted data inaccordance with rules stored in the memory, (4) predicting time-variantchanges in the status of the system by utilizing the inputted data inaccordance with the interferences made, and (5) terminating the makingof interferences in accordance with the predicted changes of the statusof the system. .Iaddend.